def make_field_chooser(x, xs, y, ys):
"""Choose values for x and y.
"""
xd = Dropdown(description='%s:' % x, values=xs)
yd = Dropdown(description='%s:' % y, values=ys)
container = VBox(children=[xd, yd])
return container
def status_printer(_, total=None, desc=None, ncols=None, img=None):
"""
Manage the printing of an IPython/Jupyter Notebook progress bar widget.
"""
# Fallback to text bar if there's no total
# DEPRECATED: replaced with an 'info' style bar
# if not total:
# return super(mytqdm, mytqdm).status_printer(file)
# fp = file
# Prepare IPython progress bar
try:
if total:
pbar = IntProgress(min=0, max=total)
else: # No total? Show info style bar with no progress tqdm status
pbar = IntProgress(min=0, max=1)
pbar.value = 1
pbar.bar_style = 'info'
except NameError:
# #187 #451 #558
raise ImportError(
"IntProgress not found. Please update jupyter and ipywidgets."
" See https://ipywidgets.readthedocs.io/en/stable"
"/user_install.html")
if desc:
pbar.description = desc
if IPYW >= 7:
pbar.style.description_width = 'initial'
# Prepare status text
ptext = HTML()
timg = HTML()
if img:
timg.value = "<br>%s<br>" % img
# Only way to place text to the right of the bar is to use a container
container = VBox([HBox(children=[pbar, ptext]), timg])
# Prepare layout
if ncols is not None: # use default style of ipywidgets
# ncols could be 100, "100px", "100%"
ncols = str(ncols) # ipywidgets only accepts string
try:
if int(ncols) > 0: # isnumeric and positive
ncols += 'px'
except ValueError:
pass
pbar.layout.flex = '2'
container.layout.width = ncols
container.layout.display = 'inline-flex'
container.layout.flex_flow = 'row wrap'
display(container)
return container
def __init__(self, model=None, model_config=None, *args, **kwargs):
# RUN HTML
self.model = model or Spectrogram(
**(model_config
or {})) #Need to access spectrogram if defaulting...
# Create alert widget (refactor into its own function?)
alert = Alert(description="Alert or something")
link((self.model, "message"), (alert, "value"))
# Create a GUI
kwargs["orientation"] = 'horizontal'
kwargs["children"] = [
HBox([
VBox([self.INOUT_panel(), self.model, alert]),
VBox([
self.plot_panel(),
self.slicing_panel(),
self.unit_panel()
]),
])
]
super(SpectraGui, self).__init__(*args, **kwargs)
self._dom_classes += ("spectroscopy row", )
def make_vgroup(children):
container = VBox(children=children)
return container
def INOUT_panel(self):
# create correlation controls. NOTE: should only be called once.
incheck = Checkbox(description='Import')
link((self.model, "inbox"), (incheck, "value"))
outcheck = Checkbox(description='Export')
link((self.model, "outbox"), (outcheck, "value"))
#loaddata = Checkbox(description="Testdata")
#link((self.model, "load_spec"), (loaddata, "value"))
#testdataset = Text(description = "")
#link((self.model, "testdataset"), (testdataset, "value"))
filename = Text(description="")
link((self.model, "file_name"), (filename, "value"))
loadbutton = Button(color='black',
background_color='AliceBlue',
description="Load")
loadbutton.on_click(lambda x: self.model.load_from_ns())
boxi = HBox([filename, loadbutton])
#link((self.model, "load_spec"), (specbox, "visible"))
# loadfile = Checkbox(description="NB Variable") #Test Data
# link((self.model, "load_file"), (loadfile, "value"))
# filebox = HBox([loadbutton, filename])
#link((self.model, "load_file"), (filebox, "visible"))
#boxi = VBox([
#HBox([loaddata, loadfile]),
#loaddata,
# specbox,
#filebox,
# ])
link((self.model, "inbox"), (boxi, "visible"))
saveplot = Button(color='black',
background_color='AliceBlue',
description='Save Plot')
saveplot.on_click(lambda x: self.model.save_plot())
savespec = Button(color='black',
background_color='AliceBlue',
description='Export Dataset')
savespec.on_click(lambda x: self.model.save_to_ns())
savespecas = Text(description="")
link((self.model, "save_spec_as"), (savespecas, "value"))
boxo = VBox([
savespecas,
HBox([saveplot, savespec]),
])
link((self.model, "outbox"), (boxo, "visible"))
#reset = Button(color='white',background_color='violet',description='Reset Defaults')
#reset.on_click(lambda x: self.model.)
#redraw = Button(description="Redraw")
#redraw.on_click(lambda x: self.model.draw())
return ControlPanel(
title="Import/Export Dataset",
children=[HBox([VBox([incheck, outcheck]),
VBox([boxi, boxo])])])
def slicing_panel(self):
""" create spectrum controls. NOTE: should only be called once."""
model = self.model #For readability
# ALL WIDGETS ARE CAPITALIZED.
#AXIS = RadioButtons(values=[0,1],description="Axis")
#link((model, "slice_axis"), (AXIS, "value"))
SPECSTART = FloatSlider(
description="Spec Start",
min=model.specslice_position_start) #Will not try to update
link((model, "specslice_position_start"), (SPECSTART, "value"))
link((model, "specstep"), (SPECSTART, "step"))
link((model, "specslider_start"),
(SPECSTART,
"min")) # Start end values (IE slider_min / slider_max)
link((model, "specslider_end"), (SPECSTART, "max"))
SPECEND = FloatSlider(
description="Spec End",
max=model.specslice_position_end) # Will not try to update
link((model, "specslice_position_end"), (SPECEND, "value"))
link((model, "specstep"), (SPECEND, "step"))
link((model, "specslider_start"), (SPECEND, "min"))
link((model, "specslider_end"), (SPECEND, "max"))
# SPACING WIDGET
SPECSPACING = IntText(description="Spec Sample by", value=1)
link((model, "specspacing"), (SPECSPACING, "value"))
TIMESTART = FloatSlider(description="Var Start",
min=model.timeslice_position_start)
link((model, "timeslice_position_start"), (TIMESTART, "value"))
link((model, "timestep"), (TIMESTART, "step"))
link((model, "timeslider_start"), (TIMESTART, "min"))
link((model, "timeslider_end"), (TIMESTART, "max"))
TIMEEND = FloatSlider(description="Var End",
max=model.timeslice_position_end)
link((model, "timeslice_position_end"), (TIMEEND, "value"))
link((model, "timestep"), (TIMEEND, "step"))
link((model, "timeslider_start"), (TIMEEND, "min"))
link((model, "timeslider_end"), (TIMEEND, "max"))
TIMESPACING = IntText(description="Var Sample by", value=1)
link((model, "timespacing"), (TIMESPACING, "value"))
speccheck = Checkbox(description="Spectral Axis")
link((model, "specbox"), (speccheck, "value"))
SPECRANGED = VBox([SPECSTART, SPECEND, SPECSPACING])
link((model, "specbox"), (SPECRANGED, "visible"))
timecheck = Checkbox(description="Variation Axis")
link((model, "timebox"), (timecheck, "value"))
TIMERANGED = VBox([TIMESTART, TIMEEND, TIMESPACING])
link((model, "timebox"), (TIMERANGED, "visible"))
return ControlPanel(
title="Slicing/Sampling",
children=[HBox([speccheck, timecheck]), SPECRANGED, TIMERANGED])
def plot_panel(self):
# create draw mode controls. NOTE: should only be called once.
cbar = Checkbox(description="Colorbar")
link((self.model, "colorbar"), (cbar, "value"))
interact = Checkbox(description="Interactive")
link((self.model, "interactive"), (interact, "value"))
plug_select = Checkbox(description="Line Selection")
link((self.model, "selectlines"), (plug_select, "value"))
autoupdate = Checkbox(description="Auto Update")
link((self.model, "autoupdate"), (autoupdate, "value"))
plugin2 = Checkbox(description='Cursor')
plugin3 = Checkbox(description='plugin3')
fwidth = FloatText(description='Plot width')
fheight = FloatText(description='Plot height')
link((self.model, "figwidth"), (fwidth, "value"))
link((self.model, "figheight"), (fheight, "value"))
f = Text(description="Function:")
link((self.model, "user_f"), (f, "value"))
fapp = Button(color='black',
background_color='AliceBlue',
description="Apply")
fapp.on_click(lambda x: self.model.apply_userf(name='apply clicked'))
#plugins = HBox([plugin1,plugin2,plugin3])
#more = Checkbox(description="More Options")### LINK IT
#link((self, "moreopt"), (more, "value"))
#popmore = Popup(children=[VBox([HBox([plug_select,plugin2,plugin3]),
# HBox([f,fapp]),
# VBox([fwidth, fheight])
# ])],
# description='Advanced', button_text='Advanced')
more = Checkbox(description="Advanced")
link((self.model, "advancedbox"), (more, "value"))
popmore = VBox([
HBox([
plug_select,
plugin2,
# plugin3
]),
HBox([f, fapp]),
HBox([fwidth, fheight])
])
link((self.model, "advancedbox"), (popmore, "visible"))
cmapcheck = Checkbox(description="Colormap")
link((self.model, "cmapbox"), (cmapcheck, "value"))
cmap = Dropdown(description="Colormap", values=self.model.COLORMAPS)
link((self.model, "colormap"), (cmap, "value"))
link((self.model, "cmapbox"), (cmap, "visible"))
colorcheck = Checkbox(description="Color")
link((self.model, "colorbox"), (colorcheck, "value"))
color = Dropdown(description="Color", values=self.model.COLORS)
link((self.model, "color"), (color, "value"))
link((self.model, "colorbox"), (color, "visible"))
kind = Dropdown(description="Plot Type", values=PLOTPARSER.keys())
link((self.model, "kind"), (kind, "value"))
return ControlPanel(title="Plot Settings",
children=[
VBox([autoupdate, kind]),
HBox([cbar, interact]),
HBox([colorcheck, cmapcheck]),
HBox([more]), cmap, color, popmore
])
def __init__(self,
model,
opt,
maxiters,
verbose=False,
current_iteration=0,
ipython_notebook=True,
clear_after_finish=False):
self.verbose = verbose
if self.verbose:
self.model = model
self.iteration = current_iteration
self.p_iter = self.iteration
self.maxiters = maxiters
self.len_maxiters = len(str(maxiters))
self.opt_name = opt.opt_name
self.model.add_observer(self, self.print_status)
self.status = 'running'
self.clear = clear_after_finish
self.update()
try:
from IPython.display import display
from IPython.html.widgets import IntProgress, HTML, Box, VBox, HBox, FlexBox
self.text = HTML(width='100%')
self.progress = IntProgress(min=0, max=maxiters)
#self.progresstext = Text(width='100%', disabled=True, value='0/{}'.format(maxiters))
self.model_show = HTML()
self.ipython_notebook = ipython_notebook
except:
# Not in Ipython notebook
self.ipython_notebook = False
if self.ipython_notebook:
left_col = VBox(children=[self.progress, self.text],
padding=2,
width='40%')
right_col = Box(children=[self.model_show],
padding=2,
width='60%')
self.hor_align = FlexBox(children=[left_col, right_col],
width='100%',
orientation='horizontal')
display(self.hor_align)
try:
self.text.set_css('width', '100%')
left_col.set_css({
'padding': '2px',
'width': "100%",
})
right_col.set_css({
'padding': '2px',
})
self.hor_align.set_css({
'width': "100%",
})
self.hor_align.remove_class('vbox')
self.hor_align.add_class('hbox')
left_col.add_class("box-flex1")
right_col.add_class('box-flex0')
except:
pass
#self.text.add_class('box-flex2')
#self.progress.add_class('box-flex1')
else:
self.exps = exponents(self.fnow, self.current_gradient)
print('Running {} Code:'.format(self.opt_name))
print(' {3:7s} {0:{mi}s} {1:11s} {2:11s}'.format(
"i", "f", "|g|", "runtime", mi=self.len_maxiters))
def __init__(self, model, opt, maxiters, verbose=False, current_iteration=0, ipython_notebook=True, clear_after_finish=False):
self.verbose = verbose
if self.verbose:
self.model = model
self.iteration = current_iteration
self.p_iter = self.iteration
self.maxiters = maxiters
self.len_maxiters = len(str(maxiters))
self.opt_name = opt.opt_name
self.model.add_observer(self, self.print_status)
self.status = 'running'
self.clear = clear_after_finish
self.update()
try:
from IPython.display import display
from IPython.html.widgets import IntProgress, HTML, Box, VBox, HBox, FlexBox
self.text = HTML(width='100%')
self.progress = IntProgress(min=0, max=maxiters)
#self.progresstext = Text(width='100%', disabled=True, value='0/{}'.format(maxiters))
self.model_show = HTML()
self.ipython_notebook = ipython_notebook
except:
# Not in Ipython notebook
self.ipython_notebook = False
if self.ipython_notebook:
left_col = VBox(children=[self.progress, self.text], padding=2, width='40%')
right_col = Box(children=[self.model_show], padding=2, width='60%')
self.hor_align = FlexBox(children = [left_col, right_col], width='100%', orientation='horizontal')
display(self.hor_align)
try:
self.text.set_css('width', '100%')
left_col.set_css({
'padding': '2px',
'width': "100%",
})
right_col.set_css({
'padding': '2px',
})
self.hor_align.set_css({
'width': "100%",
})
self.hor_align.remove_class('vbox')
self.hor_align.add_class('hbox')
left_col.add_class("box-flex1")
right_col.add_class('box-flex0')
except:
pass
#self.text.add_class('box-flex2')
#self.progress.add_class('box-flex1')
else:
self.exps = exponents(self.fnow, self.current_gradient)
print('Running {} Code:'.format(self.opt_name))
print(' {3:7s} {0:{mi}s} {1:11s} {2:11s}'.format("i", "f", "|g|", "runtime", mi=self.len_maxiters))
def optimize(self, method='HS', maxiter=500, ftol=1e-6, gtol=1e-6, step_length=1., callback=None, verbose=True):
"""
Optimize the model.
The strategy is to run conjugate natural gradients on the variational
parameters, interleaved with gradient based optimization of any
non-variational parameters. self.hyperparam_interval dictates how
often this happens.
Arguments
---------
:method: ['FR', 'PR','HS','steepest'] -- conjugate gradient method
:maxiter: int
:ftol: float
:gtol: float
:step_length: float
"""
assert method in ['FR', 'PR','HS','steepest'], 'invalid conjugate gradient method specified.'
## For GPy style notebook verbosity
if verbose:
try:
from IPython.display import display
from IPython.html.widgets import IntProgress, HTML, Box, VBox, HBox, FlexBox
self.text = HTML(width='100%')
self.progress = IntProgress(min=0, max=maxiter)
self.progress.bar_style = 'info'
self.status = 'Running'
html_begin = """<style type="text/css">
.tg-opt {font-family:"Courier New", Courier, monospace !important;padding:2px 3px;word-break:normal;border-collapse:collapse;border-spacing:0;border-color:#DCDCDC;margin:0px auto;width:100%;}
.tg-opt td{font-family:"Courier New", Courier, monospace !important;font-weight:bold;color:#444;background-color:#F7FDFA;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;border-color:#DCDCDC;}
.tg-opt th{font-family:"Courier New", Courier, monospace !important;font-weight:normal;color:#fff;background-color:#26ADE4;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;border-color:#DCDCDC;}
.tg-opt .tg-left{font-family:"Courier New", Courier, monospace !important;font-weight:normal;text-align:left;}
.tg-opt .tg-right{font-family:"Courier New", Courier, monospace !important;font-weight:normal;text-align:right;}
</style>
<table class="tg-opt">"""
html_end = "</table>"
self.ipython_notebook = True
except:
# Not in Ipython notebook
self.ipython_notebook = False
else:
self.ipython_notebook = False
if self.ipython_notebook:
left_col = VBox(children=[self.progress, self.text], padding=2, width='100%')
self.hor_align = FlexBox(children = [left_col], width='100%', orientation='horizontal')
display(self.hor_align)
try:
self.text.set_css('width', '100%')
left_col.set_css({
'padding': '2px',
'width': "100%",
})
self.hor_align.set_css({
'width': "100%",
})
self.hor_align.remove_class('vbox')
self.hor_align.add_class('hbox')
left_col.add_class("box-flex1")
except:
pass
self.start = time.time()
self._time = self.start
## ---
iteration = 0
bound_old = self.bound()
searchDir_old = 0.
iteration_failed = False
while True:
if callback is not None:
callback()
grad,natgrad = self.vb_grad_natgrad()
grad,natgrad = -grad,-natgrad
squareNorm = np.dot(natgrad,grad) # used to monitor convergence
#find search direction
if (method=='steepest') or not iteration:
beta = 0
elif (method=='PR'):
beta = np.dot((natgrad-natgrad_old),grad)/squareNorm_old
elif (method=='FR'):
beta = squareNorm/squareNorm_old
elif (method=='HS'):
beta = np.dot((natgrad-natgrad_old),grad)/np.dot((natgrad-natgrad_old),grad_old)
if np.isnan(beta) or (beta < 0.):
beta = 0.
searchDir = -natgrad + beta*searchDir_old
# Try a conjugate step
phi_old = self.get_vb_param().copy()
try:
self.set_vb_param(phi_old + step_length*searchDir)
bound = self.bound()
except LinAlgError:
self.set_vb_param(phi_old)
bound = bound_old-1
iteration += 1
# Make sure there's an increase in the bound, else revert to steepest, which is guaranteed to increase the bound.
# (It's the same as VBEM.)
if bound < bound_old:
searchDir = -natgrad
try:
self.set_vb_param(phi_old + step_length*searchDir)
bound = self.bound()
except LinAlgError:
import warnings
warnings.warn("Caught LinalgError in setting variational parameters, trying to continue with old parameter settings", LinAlgWarning)
self.set_vb_param(phi_old)
bound = self.bound()
iteration_failed = False
iteration += 1
if verbose:
if self.ipython_notebook:
t = time.time()
seconds = t-self.start
self.status = 'Running'
self.progress.bar_style = 'info'
names_vals = [['conjugate gradient method', "{:s}".format(method)],
['runtime', "{:.1f}s".format(seconds)],
['evaluation', "{}".format(iteration)],
['objective', "{:12.5f}".format(-bound)],
['||gradient||', "{:12.5f}".format(float(squareNorm))],
['beta', "{:12.5f}".format(beta)],
['status', "{:s}".format(self.status)],
]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(name)
html_body += "<td class='tg-right'>{}</td>".format(val)
html_body += "</tr>"
self.progress.value = iteration
self.text.value = html_begin + html_body + html_end
else:
print('\riteration '+str(iteration)+' bound='+str(bound) + ' grad='+str(squareNorm) + ', beta='+str(beta))
sys.stdout.flush()
# Converged yet? try the parameters if so
if np.abs(bound-bound_old) <= ftol:
if verbose:
if self.ipython_notebook:
self.status = 'vb converged (ftol)'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(name)
html_body += "<td class='tg-right'>{}</td>".format(val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'success'
else:
print('vb converged (ftol)')
if self.optimize_parameters() < 1e-1:
break
if squareNorm <= gtol:
if verbose:
if self.ipython_notebook:
self.status = 'vb converged (gtol)'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(name)
html_body += "<td class='tg-right'>{}</td>".format(val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'success'
else:
print('vb converged (gtol)')
if self.optimize_parameters() < 1e-1:
break
if iteration >= maxiter:
if verbose:
if self.ipython_notebook:
self.status = 'maxiter exceeded'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(name)
html_body += "<td class='tg-right'>{}</td>".format(val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'warning'
else:
print('maxiter exceeded')
break
#store essentials of previous iteration
natgrad_old = natgrad.copy() # copy: better safe than sorry.
grad_old = grad.copy()
searchDir_old = searchDir.copy()
squareNorm_old = squareNorm
# hyper param_optimisation
if ((iteration >1) and not (iteration%self.hyperparam_interval)) or iteration_failed:
self.optimize_parameters()
bound_old = bound
# Clean up temporary fields after optimization
if self.ipython_notebook:
del self.text
del self.progress
del self.hor_align
def optimize(self,
method='HS',
maxiter=500,
ftol=1e-6,
gtol=1e-6,
step_length=1.,
callback=None,
verbose=True):
"""
Optimize the model.
The strategy is to run conjugate natural gradients on the variational
parameters, interleaved with gradient based optimization of any
non-variational parameters. self.hyperparam_interval dictates how
often this happens.
Arguments
---------
:method: ['FR', 'PR','HS','steepest'] -- conjugate gradient method
:maxiter: int
:ftol: float
:gtol: float
:step_length: float
"""
assert method in ['FR', 'PR', 'HS', 'steepest'
], 'invalid conjugate gradient method specified.'
## For GPy style notebook verbosity
if verbose:
try:
from IPython.display import display
from IPython.html.widgets import IntProgress, HTML, Box, VBox, HBox, FlexBox
self.text = HTML(width='100%')
self.progress = IntProgress(min=0, max=maxiter)
self.progress.bar_style = 'info'
self.status = 'Running'
html_begin = """<style type="text/css">
.tg-opt {font-family:"Courier New", Courier, monospace !important;padding:2px 3px;word-break:normal;border-collapse:collapse;border-spacing:0;border-color:#DCDCDC;margin:0px auto;width:100%;}
.tg-opt td{font-family:"Courier New", Courier, monospace !important;font-weight:bold;color:#444;background-color:#F7FDFA;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;border-color:#DCDCDC;}
.tg-opt th{font-family:"Courier New", Courier, monospace !important;font-weight:normal;color:#fff;background-color:#26ADE4;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;border-color:#DCDCDC;}
.tg-opt .tg-left{font-family:"Courier New", Courier, monospace !important;font-weight:normal;text-align:left;}
.tg-opt .tg-right{font-family:"Courier New", Courier, monospace !important;font-weight:normal;text-align:right;}
</style>
<table class="tg-opt">"""
html_end = "</table>"
self.ipython_notebook = True
except:
# Not in Ipython notebook
self.ipython_notebook = False
else:
self.ipython_notebook = False
if self.ipython_notebook:
left_col = VBox(children=[self.progress, self.text],
padding=2,
width='100%')
self.hor_align = FlexBox(children=[left_col],
width='100%',
orientation='horizontal')
display(self.hor_align)
try:
self.text.set_css('width', '100%')
left_col.set_css({
'padding': '2px',
'width': "100%",
})
self.hor_align.set_css({
'width': "100%",
})
self.hor_align.remove_class('vbox')
self.hor_align.add_class('hbox')
left_col.add_class("box-flex1")
except:
pass
self.start = time.time()
self._time = self.start
## ---
iteration = 0
bound_old = self.bound()
searchDir_old = 0.
iteration_failed = False
while True:
if callback is not None:
callback()
grad, natgrad = self.vb_grad_natgrad()
grad, natgrad = -grad, -natgrad
squareNorm = np.dot(natgrad, grad) # used to monitor convergence
#find search direction
if (method == 'steepest') or not iteration:
beta = 0
elif (method == 'PR'):
beta = np.dot((natgrad - natgrad_old), grad) / squareNorm_old
elif (method == 'FR'):
beta = squareNorm / squareNorm_old
elif (method == 'HS'):
beta = np.dot((natgrad - natgrad_old), grad) / np.dot(
(natgrad - natgrad_old), grad_old)
if np.isnan(beta) or (beta < 0.):
beta = 0.
searchDir = -natgrad + beta * searchDir_old
# Try a conjugate step
phi_old = self.get_vb_param().copy()
try:
self.set_vb_param(phi_old + step_length * searchDir)
bound = self.bound()
except LinAlgError:
self.set_vb_param(phi_old)
bound = bound_old - 1
iteration += 1
# Make sure there's an increase in the bound, else revert to steepest, which is guaranteed to increase the bound.
# (It's the same as VBEM.)
if bound < bound_old:
searchDir = -natgrad
try:
self.set_vb_param(phi_old + step_length * searchDir)
bound = self.bound()
except LinAlgError:
import warnings
warnings.warn(
"Caught LinalgError in setting variational parameters, trying to continue with old parameter settings",
LinAlgWarning)
self.set_vb_param(phi_old)
bound = self.bound()
iteration_failed = False
iteration += 1
if verbose:
if self.ipython_notebook:
t = time.time()
seconds = t - self.start
self.status = 'Running'
self.progress.bar_style = 'info'
names_vals = [
['conjugate gradient method', "{:s}".format(method)],
['runtime', "{:.1f}s".format(seconds)],
['evaluation', "{}".format(iteration)],
['objective', "{:12.5f}".format(-bound)],
['||gradient||', "{:12.5f}".format(float(squareNorm))],
['beta', "{:12.5f}".format(beta)],
['status', "{:s}".format(self.status)],
]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(name)
html_body += "<td class='tg-right'>{}</td>".format(val)
html_body += "</tr>"
self.progress.value = iteration
self.text.value = html_begin + html_body + html_end
else:
print('\riteration ' + str(iteration) + ' bound=' +
str(bound) + ' grad=' + str(squareNorm) + ', beta=' +
str(beta))
sys.stdout.flush()
# Converged yet? try the parameters if so
if np.abs(bound - bound_old) <= ftol:
if verbose:
if self.ipython_notebook:
self.status = 'vb converged (ftol)'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(
name)
html_body += "<td class='tg-right'>{}</td>".format(
val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'success'
else:
print('vb converged (ftol)')
if self.optimize_parameters() < 1e-1:
break
if squareNorm <= gtol:
if verbose:
if self.ipython_notebook:
self.status = 'vb converged (gtol)'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(
name)
html_body += "<td class='tg-right'>{}</td>".format(
val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'success'
else:
print('vb converged (gtol)')
if self.optimize_parameters() < 1e-1:
break
if iteration >= maxiter:
if verbose:
if self.ipython_notebook:
self.status = 'maxiter exceeded'
names_vals[-1] = ['status', "{:s}".format(self.status)]
html_body = ""
for name, val in names_vals:
html_body += "<tr>"
html_body += "<td class='tg-left'>{}</td>".format(
name)
html_body += "<td class='tg-right'>{}</td>".format(
val)
html_body += "</tr>"
self.text.value = html_begin + html_body + html_end
self.progress.bar_style = 'warning'
else:
print('maxiter exceeded')
break
#store essentials of previous iteration
natgrad_old = natgrad.copy() # copy: better safe than sorry.
grad_old = grad.copy()
searchDir_old = searchDir.copy()
squareNorm_old = squareNorm
# hyper param_optimisation
if ((iteration > 1) and not (iteration % self.hyperparam_interval)
) or iteration_failed:
self.optimize_parameters()
bound_old = bound
# Clean up temporary fields after optimization
if self.ipython_notebook:
del self.text
del self.progress
del self.hor_align